Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model.
| Title: | Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model. |
|---|---|
| Authors: | Deng, Yating1,2,3 (AUTHOR), Zhu, Hongkai1,2,3 (AUTHOR), Peng, Hongling1,2,3,4 (AUTHOR) penghongling@csu.edu.cn |
| Source: | Clinical & Experimental Medicine. 1/17/2025, Vol. 25 Issue 1, p1-16. 16p. |
| Subject Terms: | *PLASMA cell leukemia, *MEDICAL sciences, *PLASMA cells, *DISEASE risk factors, *MULTIPLE myeloma |
| Abstract: | Multiple myeloma (MM) is characterized by clonal plasma cell proliferation in the bone marrow, challenging prognosis prediction. We developed a gene-pairing prognostic risk model using m6A regulatory genes and a nested LASSO method. A cutoff of − 0.133 categorized MM samples into high-risk and low-risk groups. The model showed strong prognostic performance in 2088 newly diagnosed MM samples and predicted response to combination therapy (daratumumab, carfilzomib, lenalidomide, and dexamethasone) in patients who failed or relapsed from bortezomib-containing regimens, with an AUC of 0.9. It distinguished between smoldering MM and MM (cutoff: − 0.45) and between MM and plasma cell leukemia (cutoff: 0.0857). Single-cell analysis revealed higher risk scores at relapse. Combining MM cell lines and sample data, we identified potential drugs and targets (ADAT2 and NUP153) effective against high-risk MM. Integrating the m6A risk model with the International Staging System (ISS) enhanced stratification accuracy. These insights support precision treatment of MM. [ABSTRACT FROM AUTHOR] |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Deng%2C+Yating%22">Deng, Yating</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhu%2C+Hongkai%22">Zhu, Hongkai</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Hongling%22">Peng, Hongling</searchLink><relatesTo>1,2,3,4</relatesTo> (AUTHOR)<i> penghongling@csu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Clinical+%26+Experimental+Medicine%22">Clinical & Experimental Medicine</searchLink>. 1/17/2025, Vol. 25 Issue 1, p1-16. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22PLASMA+cell+leukemia%22">PLASMA cell leukemia</searchLink><br />*<searchLink fieldCode="DE" term="%22MEDICAL+sciences%22">MEDICAL sciences</searchLink><br />*<searchLink fieldCode="DE" term="%22PLASMA+cells%22">PLASMA cells</searchLink><br />*<searchLink fieldCode="DE" term="%22DISEASE+risk+factors%22">DISEASE risk factors</searchLink><br />*<searchLink fieldCode="DE" term="%22MULTIPLE+myeloma%22">MULTIPLE myeloma</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Multiple myeloma (MM) is characterized by clonal plasma cell proliferation in the bone marrow, challenging prognosis prediction. We developed a gene-pairing prognostic risk model using m6A regulatory genes and a nested LASSO method. A cutoff of − 0.133 categorized MM samples into high-risk and low-risk groups. The model showed strong prognostic performance in 2088 newly diagnosed MM samples and predicted response to combination therapy (daratumumab, carfilzomib, lenalidomide, and dexamethasone) in patients who failed or relapsed from bortezomib-containing regimens, with an AUC of 0.9. It distinguished between smoldering MM and MM (cutoff: − 0.45) and between MM and plasma cell leukemia (cutoff: 0.0857). Single-cell analysis revealed higher risk scores at relapse. Combining MM cell lines and sample data, we identified potential drugs and targets (ADAT2 and NUP153) effective against high-risk MM. Integrating the m6A risk model with the International Staging System (ISS) enhanced stratification accuracy. These insights support precision treatment of MM. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Clinical & Experimental Medicine is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10238-024-01526-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 1 Subjects: – SubjectFull: PLASMA cell leukemia Type: general – SubjectFull: MEDICAL sciences Type: general – SubjectFull: PLASMA cells Type: general – SubjectFull: DISEASE risk factors Type: general – SubjectFull: MULTIPLE myeloma Type: general Titles: – TitleFull: Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Deng, Yating – PersonEntity: Name: NameFull: Zhu, Hongkai – PersonEntity: Name: NameFull: Peng, Hongling IsPartOfRelationships: – BibEntity: Dates: – D: 17 M: 01 Text: 1/17/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 15918890 Numbering: – Type: volume Value: 25 – Type: issue Value: 1 Titles: – TitleFull: Clinical & Experimental Medicine Type: main |
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